• The Korean Journal of Financial Management
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• v.19 no.2
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• pp.49-75
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• 2002

본 연구는 과거의 수익률에 근거한 투자전략인 반대투자 전략과 모멘팀 전략의 성과를 분석 하고 있다. 이러한 투자전략의 성과와 주식수익률의 시계열적 특성간의 관련성을 밝히고, 투자 성과를 기업고유 요인에 대한 주가의 과잉반응, 시장의 공통요인에 대한 주가의 반응, 그리고 개별주식의 평균수익률의 횡단면적 공분산에 기인한 부분으로 각각 분해하고 있다. 모멘팀 전략은 1주일 이상 6개월 정도의 포트폴리오 재구성 기간에 대하여 양의 성과를 보이고 있으며, 반대투자 전략은 3개월 이상 6개월의 정도의 기간에 대하여 유의적인 성과가 나타나고 있지만, 상승국면에서는 양의 성과가 나타나고 하락국면에서는 음의 성과가 나타나고 있다. 투자전략의 성과는 1주일 이내의 기간에 대해서는 수익률의 자기공분산에 의하여 주로 설명되며, 1개월에서 3개월 정도의 기간에 대해서는 교차공분산에 의하여 주로 설명되고, 6개월의 기간에 대해서는 개별주식 평균수익률의 횡단면적 분산에 의하여 주로 설명되고 있는 것으로 나타났다. 기간이 짧은 경우에는 투자성과가 주로 기업고유 요인에 대한 지연된 반응에 의하여 설명되며, 기간이 길어짐에 따라 주식수익률은 기업고유 요인에 대하여 과잉반응하는 것으로 나타나고 있다. 시장의 공통요인에 대해서 대체로 지연된 반응이 나타나며 기간이 길어짐에 따라 소규모기업의 주식은 시장의 공통정보에 대하여 과잉반응하는 것으로 나타났다.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Management & Information Systems Review
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• v.32 no.1
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• pp.63-85
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• 2013

This study tries to investigate the fundamental implications inherent in inventory asset information(specifically, unexpected inventory investment) by analyzing how the relationship between unexpected inventory investment and future operating performance. And we study how is the response of the stock market participants to the fundamental implications inherent in inventory asset information. Prior papers often assume the efficient market and they view the significant relation between stock prices and financial indicators as evidence of the contribution of such indicators to future earnings. Leading indicators are attracting the market's attention for equity valuation. We study whether one leading indicator (unexpected Inventories) forecasts future earnings, and whether market participants fully reflect the predictive ability when they sets share prices(Mishkin test, 1983). Our empirical results of the study are summarized as follows. Current unexpected inventory investment is negatively associated with future operating performance. Also, our evidence is that the stock market participants overprice the contribution of unexpected inventory investment when predicting future earnings. Furthermore, a hedge strategy that uses the overpricing gives significant future abnormal returns. The overall results help the users of financial reports, researchers of accounting, and the accounting principle setting body.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1049-1060
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• 2009

The expansion of volatility in Korean Stock Market made it more difficult for the individual to invest directly and increased the weight of indirect investment through a fund. The purpose of this study is to construct the EIF(enhanced index fund) model achieves an excessive return among several types of fund. For this purpose, this paper propose portfolio optimization model to manage an index fund by using GA(genetic algorithm), and apply the trading amount and the closing price of standard index to earn an excessive return add to index fund return. The result of the empirical analysis of this study suggested that the proposed model is well represented the trend of KOSPI 200 and the new investment strategies using this can make higher returns than Buy-and-Hold strategy by an index fund, if an appropriate number of stocks included.

• Cartoon and Animation Studies
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• s.40
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• pp.287-314
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• 2015

This study tries to analyze the portfolio of production budget related to Hollywood animation movies released during the five years between 2010 and 2014, in order to investigate how blockbuster strategy made the box office performance. The analysis shows that this animation genre invested more than one thousand million dollars as the average budget for each film. It increased threefold in the box office result. In the production of Hollywood animation genre, 72.2% of its whole production money was found to use for movies investing more than one thousand million dollars. It is to show how the production of animation aimed for profit-making via blockbuster strategy recognized as the most successful portfolio strategy in the recent Hollywood film industry.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.572-577
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• 2008

In order to apply strategic advanced project management to the Korean construction industry, the study conducted a comparative analysis of the project management body of knowledge of the advanced countries such as the USA and Japan as well as Europe. As a result, it was found that the connection to 'execution' of 'strategy' was highlighted as a common main issue in the theoretical background of project management body of knowledge, and strategic planning, which aligns 'program management' based on the integration of multiple project management and operations in single project with 'portfolio management' for selection and concentration, has been emphasized. Accordingly, the study built up the framework for the application of strategic advanced project management for strategic action in the Korean construction industry and proposed the following applicable solutions for implementation into the current Korean construction industry: 1) Innovate global competitiveness by preparing an 'ideology and philosophy' for the strategic action of an organization, 2) Establish a strategic 'environment' in consideration of the culture and structure of an organization, 3) Propose a strategic 'vision' for attaining a realizable goal within an organization, 4) Create an 'investment' on the portfolio in line with the strategy, 5) 'Execute' the program through the portfolio and project management. Lastly, the study brought up strategies for sustainable growth by applying strategic advanced project management to the Korean construction industry with a view to acquiring 'Performance' through the implementation and operation of their integrated system.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.465-477
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• 2015

Today's companies build strong brand assets which, through the expansion of other business areas, promote efficient corporate management. Many companies manage brand assets among through a multitude of brand groups using brand portfolios rather than the single brand strategy. Such brand group influence can be related not only to brand group expansion, but also to parent company brands and product brand groups. The purpose of this study was to identify the effects of parent corporate brand associations on brand portfolio evaluation. The results of the present study is as follows: positive parent corporate brand image was revealed to play a positive role in brand portfolio evaluation. Parent corporate brand image provided endorsement for their product brands, and this can reduce consumer's decision cost on brand portfolio evaluations. This study focused on two types of brand relationship strategy : brand expansion strategy and individual brand strategy. With individual brand strategy, cases where parent company brands provided endorsement and cases to the contrary were studied separately. In cases where well-managed parent corporate brand image were able to provide endorsement in the case of individual brand strategy like that of brand expansion strategy.

• Journal of Korean Library and Information Science Society
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• v.38 no.4
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• pp.441-462
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• 2007

As country try expand R&D investment and enhance its efficiency to improve the national competitiveness, research is needed to conduct qualitative enhancement and derive progressive future strategy in relation to the academic information distribution project in scientific technology field. In this study, BSC-based performance indicators were applied to an institute that is the representative of domestic academic information distribution institutes in the field of scientific technology to evaluate project performance, and then to analyze portfolio of using such evaluation results. As for the items of evaluation for the performance indicators of academic information distribution project in the scientific technology field, 12 items that includes information resource quality, information service quality, user satisfaction and economically useful value of academic information from four(4) viewpoints such as information resource, information service, user and economic viewpoints. In the portfolio analysis, it was conducted by performance indicators and by elements of the individual performance indicators as well. Based on the results of performance evaluation and portfolio analysis, the improvement method by viewpoints on academic information distribution project of an institute was suggested.

• The Korean Journal of Financial Studies
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• v.9 no.1
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• pp.163-187
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• 2003

본 연구는 옵션가격 및 거래량 자료를 이용하여 옵션시장의 가격발견 기능에 대해서 분석을 시도하였다. 이를 위해 먼저 옵션가격과 거래량 정보가 현물시장을 선행하는 현상에 대해서 분석해 보았다. 옵션가격은 실제 현물지수를 약 1시간 정도 선행하는 것으로 관찰되었다. 콜옵션 가격이 풋옵션에 비해서 상대적으로 옵션시장에서 높게 거래되는 경우 이는 현물주식시장에서의 주가상승을 예고하는 것으로 나타났다. 옵션 거래량 정보 역시 현물시장의 가격움직임을 예측하는데 유효한 것으로 관찰되었다. 콜옵션의 풋옵션 대비 상대적인 거래증가는 투자자의 낙관적인 장세전망을 반영해 일단 현물지수의 상승을 야기하는 것으로 나타났으나 이후 투자자의 풋옵션을 통한 헤지(hedge) 수요의 증가로 이어지는 것으로 조사되었다. 두 번째로 본 연구는 이러한 옵션시장의 가격발견 기능을 이용하여 매매전략을 수립하고 이를 통하여 투자이익을 극대화시킬 수 있는지에 대해서 살펴보았다. 콜옵션 가격(거래량)이 풋옵션 가격(거래량)에 비해 고평가(증가) 되었을 경우 이는 주가상승을 미리 예고하고 있는 신호로 받아들어져 주식을 매입하고 반대로 콜옵션 가격(거래량)이 풋옵션 가격(거래량)에 비해 저평가(감소) 되었다면 주가하락을 예측하기 때문에 주식을 매도함으로써 투자이익을 증대시킬 수 있을 것이다. 실증분석 결과는 우선 옵션 가격정보를 이용하여 현물시장에서 지수 바스켓 포트폴리오를 매매하려는 전략은 30분 내외의 단기 투자에는 유효하나 그 이상의 투자기간을 가지는 경우에는 예상과는 다른 결과를 초래하였다. 반면 옵션시장에서의 콜옵션과 풋옵션의 상대적인 거래량 정보는 현물주식시장의 움직임을 예측하는데 옵션 가격정보에 비해서 보다 효과적인 것으로 판단되었다. 조사한 모든 일중 및 1일(overnight) 투자수익률에서 옵션 거래량의 상대적 비율에 의거한 투자전략은 통계적으로 유의한 투자수익률의 차이를 가져왔다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.453-456
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• 2000

고정금리 상품의 투자에서 이자율 변동 위험을 피할 수 있는 방법으로 많이 쓰이는 것은 듀레이션을 이용한 면역 모델(Bond Portfolio Immunization Model)로, 이것은 이자율 변동에 대해 포트폴리오의 가격 민감도인 듀레이션을 이용하여 자산과 부채의 변화를 일치시키는 방법이다. 그러나 이 전략은 수익률 곡선이 평형하게 이동한다는 가정(Parallel Shift Term-Structure)을 단점으로 가지고 있어 현실에 적용될 경우 오차가 발생하게 된다. 본 연구에서는 선험적(empirical) 방법으로 평형하지 않은 움직임을 가진 기간구조의 함수(Term-Structure Function)를 정의하고 면역 모델을 부채의 현금흐름에 대해 개별적으로 적용하는 새로운 면역 전략 모델을 구성하고 실험한다